Indian Ocean Dipole: Processes and impacts
P N VINAYACHANDRAN1,∗ , P A FRANCIS2 and S A RAO3
1
Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore 560 012, India
2
Indian National Centre for Ocean Information Services, Hyderabad 500 055, India
3
Indian Institute of Tropical Meteorology, Pashan, Pune 411 008, India
∗
e-mail: vinay@caos.iisc.ernet.in
Equatorial Indian Ocean is warmer in the east, has a deeper thermocline and mixed layer, and
supports a more convective atmosphere than in the west. During certain years, the eastern Indian
Ocean becomes unusually cold, anomalous winds blow from east to west along the equator and
southeastward off the coast of Sumatra, thermocline and mixed layer lift up and the atmospheric
convection gets suppressed. At the same time, western Indian Ocean becomes warmer and enhances
atmospheric convection. This coupled ocean-atmospheric phenomenon in which convection, winds,
sea surface temperature (SST) and thermocline take part actively is known as the Indian Ocean
Dipole (IOD). Propagation of baroclinic Kelvin and Rossby waves excited by anomalous winds,
play an important role in the development of SST anomalies associated with the IOD. Since mean
thermocline in the Indian Ocean is deep compared to the Pacific, it was believed for a long time
that the Indian Ocean is passive and merely responds to the atmospheric forcing. Discovery of the
IOD and studies that followed demonstrate that the Indian Ocean can sustain its own intrinsic
coupled ocean-atmosphere processes. About 50% percent of the IOD events in the past 100 years
have co-occurred with El Nino Southern Oscillation (ENSO) and the other half independently.
Coupled models have been able to reproduce IOD events and process experiments by such models –
switching ENSO on and off – support the hypothesis based on observations that IOD events develop
either in the presence or absence of ENSO. There is a general consensus among different coupled
models as well as analysis of data that IOD events co-occurring during the ENSO are forced by
a zonal shift in the descending branch of Walker cell over to the eastern Indian Ocean. Processes
that initiate the IOD in the absence of ENSO are not clear, although several studies suggest that
anomalies of Hadley circulation are the most probable forcing function. Impact of the IOD is felt in
the vicinity of Indian Ocean as well as in remote regions. During IOD events, biological productivity
of the eastern Indian Ocean increases and this in turn leads to death of corals over a large area.
Moreover, the IOD affects rainfall over the maritime continent, Indian subcontinent, Australia and
eastern Africa. The maritime continent and Australia suffer from deficit rainfall whereas India and
east Africa receive excess. Despite the successful hindcast of the 2006 IOD by a coupled model,
forecasting IOD events and their implications to rainfall variability remains a major challenge as
understanding reasons behind an increase in frequency of IOD events in recent decades.
1. Introduction
Monsoons dominate the climate of the North
Indian Ocean and the neighbouring land mass.
Winds over the Indian Ocean (figure 1) blow from
the southwest during May–September and northeast during November–February and drive a circulation that reverses its direction completely, unseen
in any other part of the world oceans (Schott
and McCreary 2001; Shankar et al 2002). Because
Keywords. Indian Ocean Dipole; oceano graphy; interannual variability.
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P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
Figure 1. Climatology of winds (vectors in m/s), SST (◦ C, color shaded) and outgoing longwave radiation (OLR, contours
in Wm−2 ) over the Indian Ocean.
of monsoons, the spatial distribution of sea surface temperature (SST) in the Indian Ocean is
characterised by warm water on the eastern side
and cooler on the west which is in contrast to
Pacific and Atlantic Oceans that are warmer on
the west. In fact, all characteristic properties of
the ocean show marked east-west asymmetry in
Indian Ocean. Freshwater input into the ocean,
in the form of rain and drainage from the land,
is greater on eastern side causing the eastern part
of the basin to have lower salinity than the west.
A major upwelling system is located off the western boundary and consequently biological productivity is higher in the west than in the east. The
thermocline, which separates warmer water of the
oceanic mixed layer from the colder water underneath, is located deeper in the east than in the
west. Asymmetry in the SST also influences the
overlying atmosphere: convection is higher over
the eastern part of the ocean and lesser over the
west (figure 1).
The equatorial Indian Ocean, however, experiences a somewhat different seasonal wind forcing and hence has a different response than the
Arabian Sea and Bay of Bengal. Winds over
the equatorial Indian Ocean, particularly their
zonal component, are weak during monsoons. Relatively strong westerly winds, however, appear during the transition between monsoons, first during
April-May (spring) and then again during OctoberNovember (fall). These winds drive strong eastward currents along the equator, attaining speeds
exceeding 1 ms−1 , known as Wyrtki (1973) jets.
Wyrtki jets transport warmer upper layer water
towards the east, which accumulates near the
boundary causing the thermocline in the east
to be deeper than in the west. The thermocline
slope becomes greater during spring and fall and
the volume of warm water and the heat content
of the Indian Ocean is larger on the eastern side
than in the west. When the thermocline is shallow,
winds have to do lesser work to bring cooler water
into the mixed layer than when it is deep. That
is, for the same wind-strength, a shallower thermocline can facilitate cooling of the mixed layer
and SST, whereas a deeper thermocline may not.
Thus, Wyrtki jets dictate the shape of the thermocline in the equatorial Indian Ocean. Climatologically, since the eastern equatorial Indian Ocean is
warmer, it supports a more convective atmosphere
than in the west (figure 1). The departure of
the ocean-atmosphere system from this mean
state occurring during certain years, characterized
by opposite sign of anomalies in the east and west,
is known as the Indian Ocean Dipole (IOD).
Possibilities of air-sea coupled processes over
the Indian Ocean have been suggested by several
studies in the past. Reverdin et al (1986) analyzed
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
interannual variations of convection and SST in
the equatorial Indian Ocean using ship reports.
They suggested that coupled air-sea dynamics over
the Indian Ocean should be considered in order to
understand the interannual variability. This suggestion was prompted by anomalous conditions
in 1961, characterized by significantly cold SST
anomalies in the east (between 80◦ E–90◦ E) and
warm SST anomalies (SSTA) in the west. From
limited ship observations, Reverdin et al (1986)
concluded that the SSTA affects cloudiness, rainfall
and consequently, causes westward wind anomalies
along the equator. Anomalies during 1961 were not
concurrent with an ENSO which pointed to the role
of air-sea interaction processes controlled by Indian
Ocean. Hastenrath et al (1993) showed that zonal
structure of the equatorial Indian Ocean responds
to changes in the strength of westerlies occurring during the transition from summer to winter
monsoon (October-November). Stronger westerlies
drive a faster equatorial jet causing deeper mixed
layer and warmer SSTs in the east and entails
cold water upwelling in the western equatorial
Indian Ocean. Changes in the ocean state affect
the atmosphere, particularly rainfall over eastern
Africa. SST variability in the eastern Indian Ocean
during 1994 was observed to have strong coupling
to the shallowing of the thermocline (Meyers 1996).
The shallow thermocline during 1994 was due to
unusually weak equatorial jets (Vinayachandran
et al 1999) caused by anomalous easterly winds.
Saji et al (1999) recognised anomalous conditions
such as in 1961, 1994 and 1997 in the tropical
Indian Ocean as a dipole mode characterized by
low SST off Sumatra and high SST in the western equatorial Indian Ocean accompanied by wind
and rainfall anomalies. They showed that the IOD
is a coupled ocean atmosphere phenomenon, it
is independent of ENSO and about 12% of the
SST variability in the Indian Ocean was associated
with the dipole mode. Highlighting the 1997–98
event Webster et al (1999) also have suggested that
anomalous conditions present during this period
was due to an internal mode of the climate system
of the Indian Ocean. A coupled ocean atmosphere
process in which oceanic Rossby waves cause a
deepening of the thermocline was proposed to be
a necessary feature that led to the sequence of
events culminating in anomalies that contrast the
in east-west direction (Webster et al 1999). The
ocean-atmosphere coupling during an IOD involves
atmospheric convection, winds, SST and upper
ocean dynamics. The discovery of the IOD led to
the recognition that the Indian Ocean can support its own coupled ocean-atmosphere variations
(Schott et al 2009) and is not merely a slave to the
events happening over the Pacific Ocean in connection with ENSO.
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The Indian Ocean circulation and its impact on
regional climate has been a topic of great interest
recently and several reviews have appeared in the
literature. The monsoon circulation of the Indian
Ocean has been reviewed by Schott and McCreary
(2001). Yamagata et al (2004) and Annamalai and
Murtugudde (2004) have reviewed the interannual
variability in the Indian Ocean and its impact on
climate variability. The role of tropical Atlantic,
Pacific and Indian Oceans on climate variability
in the tropics has been reviewed by Chang et al
(2006). In a recent review, Schott et al (2009) have
summarized the role of Indian Ocean circulation
on climate variability. It is well recognised that
the dominant signal of coupled interannual variability in the Indian Ocean is the IOD. The objective
of this review is to summarize our understanding
of the IOD, particularly the processes associated
with IOD events and their implications, considering that there has been rapid development in our
understanding of these. A description of the IOD
phenomenon is given in the next section followed
by a section devoted to processes related to IOD.
The relationship between ENSO and IOD is discussed in section 4, followed by mechanisms that
can trigger IOD in section 5. Section 6 summarizes
the impact of IOD on regional climate and outstanding issues are listed in section 7.
2. Indian ocean dipole
The Indian Ocean Dipole refers to an anomalous
state of the ocean-atmosphere system (Saji et al
1999; Webster et al 1999; Murtugudde et al 2000).
During the mature phase of an IOD, which happens during September-October, eastern equatorial
Indian Ocean becomes unusually cold and the
western equatorial Indian Ocean unusually warm
(figure 2). Cold SSTA suppress atmospheric convection in the east whereas warm SSTA enhance
convection in the west. Winds blow westward
over the equatorial Indian Ocean and from the
southwest off the coast of Sumatra, the latter
being favourable for coastal upwelling. Equatorial
jets become weak, reducing the eastward transport of warm water entailing a shallower than
usual thermocline in the east. Sea level decreases
in the eastern equatorial Indian Ocean and rises
in the central part. Thermocline rises in the
east and deepens in the central and western
equatorial Indian Ocean. Temperature anomalies
associated with IOD are also seen in subsurface
ocean (Vinayachandran et al 2002; Horii et al
2008) and the sub-surface signals are strongly coupled to surface signals (Rao et al 2002). Due
to the vertical movement of isotherms, magnitude of temperature anomalies at any given depth
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P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
Figure 2. Mean September-October composite anomaly patterns of (a) SST (◦ C, shaded) and depth of 20◦ C isotherm
(m, contours) and (b) OLR (Wm−2 , shaded) and surface winds (ms−1 , vectors) for the positive IOD years during 1979–2008
for which satellite data of OLR is available. The composite is based on positive IOD years (Meyers et al 2007) of 1982,
1991, 1994, 1997 and 2006. SST data used is HadISST available at (http://badc.nerc.ac.uk); depth of 20◦ C isotherm is
derived from simple ocean data assimiliation (SODA, Carton et al 2000) available at (http://iridl.ldeo.columbia.edu); NOAA
AVHRR OLR data and NCEP Reanalysis surface wind data are obtained from (http://www.cdc.noaa.gov).
Figure 3.
and 1992.
Same as in figure 2, but for negative IOD years since 1979 listed in Meyers et al (2007), i.e. 1980, 1981, 1985
is much greater than at the surface. Anomalous
state of the ocean-atmosphere system described
above is referred to as a positive IOD (pIOD).
The reverse, negative IOD (nIOD), also occurs,
characterized by warmer SSTA, enhanced convection, higher sea level, deeper thermocline in the
east and cooler SSTA, lower sea level, shallower
thermocline and suppressed convection in the west
(figure 3). Negative IOD can be considered as an
intensification of the normal state whereas positive IOD represents conditions nearly opposite to
the normal. Therefore, major focus of attention
has been to understand pIOD. This article concerns mostly with pIOD events and for simplicity,
is referred to as IOD hereafter.
An IOD event can be detected using Dipole
Mode Index (DMI) which is defined as the
difference in SST anomalies between western
and eastern equatorial Indian Ocean (figure 4).
Averages of anomalies are calculated for a box in
the western Indian Ocean bounded by 50◦ E–70◦ E
and 10◦ S–10◦ N and in the east by 10◦ S–Equator
and 90◦ E–110◦ E. In general, the DMI is expected
to be higher than one standard deviation and
should remain so for 3 to 4 months, in an IOD year.
The west minus east anomalies are positive during
a pIOD year and vice versa. During the 1870–1999
period, 27 pIOD events occurred and recent IOD
events are 1961, 1963, 1967, 1972, 1982, 1994, and
1997 (Yamagata et al 2002; Vinayachandran et al
2007). During 2003, a pIOD event was initiated
but terminated midway (Rao and Yamagata 2004).
Most recently, an IOD event occurred during 2006
(Vinayachandran et al 2007). Twenty nIOD events
have also occurred during the 1870–1999 period
(Meyers et al 2007).
Evolution of the IOD (figure 5) is strongly locked
to the seasonal cycle due to the thermodynamic
air-sea feedback between an atmospheric anticyclone located to the east of Sumatra (Annamalai
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
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Figure 4. The dipole mode index (DMI) defined (Saji et al 1999) as the difference in SST anomalies between western
(50◦ E–70◦ E) and eastern (90◦ E–110◦ E) Indian Ocean. The DMI is normalized by its standard deviation and smoothed by
a 5-month running mean before plotting.
Figure 5. Monthly mean composite anomaly patterns of SST and depth of 20◦ C for the pIOD years. Alternate months
starting from March in the pIOD year are plotted. The top right panel corresponds to January of the year following pIOD.
et al 2003) and the ocean underneath being dependent on the seasonal cycle of winds (Li et al 2003).
Typically, an event begins to appear during late
spring/early summer, matures during September–
November and most of the anomalies disappear
by January of the following year. Easterly equatorial wind anomalies and warm SST anomalies
in the central part of the Indian Ocean begin to
appear during spring (figure 6). SST anomalies
associated with the IOD peak during September–
November. For certain events, however, there is
a clear indication that the atmospheric component appears much earlier in spring in the form
of easterly wind anomalies and southeasterlies
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P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
Figure 6. Monthly mean composite anomaly patterns of OLR (Wm−2 , shaded) and surface wind (ms−1 , vectors) for
the pIOD years. Alternate months starting from March in the pIOD year are plotted. The top right panel corresponds to
January of the following year of pIOD.
off Sumatra (Vinayachandran et al 1999, 2007).
Even though the general features of every event
are similar, there are differences in the location
and timing of the peak anomalies. For example,
the peak SST anomalies during the 1994 event
occurred about two months earlier compared to
the 1997 event. The eastern pole is located more
or less in the same region for every event because
coastal upwelling is an important cooling mechanism. In the west, however, regions covered by positive anomalies vary considerably between events.
During the 2006 event, for example, positive SSTA
were located to the west of the commonly considered IOD box bounded by 50◦ E–70◦ E; 10◦ S–10◦ N
(Vinayachandran et al 2007).
Copious upwelling takes place along the eastern
coast of the EIO during an IOD which leads
to enhanced biological productivity and affects
the bio-geochemistry of the region. The satellite data coverage of chlorophyll concentration
is restricted to the events of 1997–98 and 2006
(Wiggert et al 2009; Iskandar et al 2009). During the strong IOD event of 1997–98, the eastern
equatorial Indian ocean, which is not usually very
productive, experienced phytoplankton blooms
(Murtugudde and Busalachhi 1999). This event
was also associated with an increase in chlorophyll a concentration in the southeastern Bay
of Bengal, and a decrease in the southwestern
part of the bay (Vinayachandran and Mathew
2003). In the Arabian Sea, influence of IOD led
to a decrease in chlorophyll a concentration, primary productivity and sea to air CO2 flux (Sarma
2006). Chlorophyll concentration in the western Indian Ocean and along the coast of India
shows a decrease during the IOD years of 1997
and 2006 (Wiggert et al 2006). Enhanced biological productivity off the coast of Indonesia during
1997 led to the death of coral reef in a large
area due to the asphyxia caused by the oxidation
of organic matter in the water column (Abram
et al 2003).
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
Coral records have provided evidences for the
presence of IOD in the present as well as in
the past because upwelling and cooling taking
place in the eastern ocean during IOD events
leave their signatures in the marine environment,
which are preserved in coral records. Anomalies of
Sr/Ca indicate temperature anomalies in the ocean
whereas δO18 indicates influence of both temperature and salinity. Such records from Mentawai
Islands off Indonesia showed that several IODs
occurred in the past, including an event in 1877
which was stronger than that during 1997 (Abram
et al 2003). On the western side, coral density
bands of Malindi Marine Park, Kenya also present
evidences of the IOD (Kayanne et al 2006). Here,
anomalies of δO18 were correlated with the increase
in rainfall during IOD events. The Sr/Ca ratio and
δO18 (after removing temperature signals) from
coral records carry distinct signals of temperature
and salinity anomalies respectively, and therefore,
can be used for reconstructing past records of IOD
(Abram et al 2008). Such records show that the
IOD during middle holocene were characterized
by longer duration of surface cooling caused by
enhanced cross equatorial winds.
3. Processes
Evolution of SST anomalies involves coupled
ocean-atmosphere processes (Vinayachandran
et al 1999; Murtugudde and Busalacchi 1999;
Vinayachandran et al 2002). Oceanic processes
that are responsible for cooling SST anomalies
are: (1) shoaling of thermocline and (2) variations in mixed layer depth. The first process
depends chiefly on subsurface ocean dynamics
(i.e., coastal and open ocean upwelling), while
the second one helps in re-distributing the heat
energy in the top few meters of the ocean. Similarly, atmospheric processes that are involved in
evolution of SST are (1) atmosphere-ocean heat
fluxes and (2) large-scale atmospheric circulations.
In order to understand the role of oceans and
atmosphere in evolution of SST anomalies during
IOD events, we describe oceanic and atmospheric
processes separately in this section, focussing on
their major contributions to SST anomalies.
3.1 Oceanic processes
Ocean general circulation models (OGCM) have
provided useful insights into processes that lead
to the development of SSTA during IOD events
(Murtugudde et al 2000; Vinayachandran 2002).
Forced by winds and surface fluxes, they have been
able to simulate the evolution of IOD extremely
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well (Vinayachandran et al 2007). Such models
have illustrated that upwelling, forced either by
winds or through the propagation of baroclinic
waves, is an important process responsible for SST
cooling in the east. The semiannual zonal winds
over the central equatorial Indian Ocean drive eastward equatorial jets. Anomalies in zonal winds
weaken or even reverse the Wyrtki jet, which
causes a decrease in eastward transport resulting
in a shallow thermocline in the east (Hastenrath
et al 1993; Vinayachandran et al 1999). Alongshore component of winds effectively upwells cooler
water to the mixed layer when the thermocline
is shallow. Air-sea fluxes also play a significant
role in the SST cooling, particularly during initial
stages of IOD development (Vinayachandran et al
2007). The western warming is mostly controlled
by air-sea fluxes and advection by ocean currents.
Anomalous downwelling Rossby waves deepen the
thermocline which prevents cooling of the SST by
entrainment (Murtugudde et al 2000). The role of
waves is elaborated further below.
3.2 Role of baroclinic waves
The semiannual zonal winds over the central equatorial Indian Ocean excite Kelvin waves which
remotely affect sea level variations and thermal structure along the eastern equatorial Indian
Ocean (Clarke and Liu 1993; Yamagata et al 1996;
Meyers 1996). Easterly wind anomalies along the
equator drive an anomalous upwelling Kelvin wave
which radiates into the eastern Indian Ocean.
After reaching the eastern basin they reflect
into coastally trapped Kelvin and Rossby waves.
This upwelling Kelvin wave lifts up the thermocline in the eastern equatorial Indian Ocean
thereby triggering upwelling in the southeastern tropical Indian Ocean (SETIO) (Vinayachandran et al 1999; Murtugudde et al 2000; Vinayachandran et al 2002; Rao et al 2002). Local
alongshore winds, which are southeasterly during
development and peak phase of the Indian Ocean
Dipole, also drive the coastal upwelling in the
SETIO (Vinayachandran et al 1999; Murtugudde
et al 2000). Due to the strong easterly anomalies along equator and southeasterly winds along
Sumatra/Java coasts, strong anomalous anticyclonic wind stress curl forms in the southern tropical Indian Ocean (Xie et al 2002). This anomalous
wind stress curl forces downwelling Rossby waves in
the southern tropical Indian Ocean during developing phase of the IOD (Rao and Behera 2005). Similarly, downwelling Rossby waves are formed in the
northern tropical Indian Ocean. In normal years
open-ocean upwelling also occurs in the southwestern tropical Indian Ocean forced by negative
wind stress curl (Masumoto and Meyers 1998; Xie
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P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
Figure 7. First EOF mode of sea level anomalies from
SODA (upper panel). Positive Indian Ocean Dipole events
are marked as I in the corresponding time series (lower
panel).
et al 2002). Downwelling Rossby waves radiated
from the southeastern Indian Ocean propagate into
this upwelling region, deepen the thermocline and
warm the SST in the western tropical Indian Ocean
(Murtugudde et al 2000; Vinayachandran et al
2002). These features are brought out clearly in a
simple empirical orthogonal function (EOF) analysis of sea level anomalies obtained from SODA
(Carton et al 2000). The first EOF mode of sea level
anomalies clearly shows the structure of Kelvin and
Rossby waves in the tropical Indian Ocean. During
IOD years, the anomalous upwelling Kelvin waves
propagate eastward, reflect and then propagate as
coastal trapped Kelvin waves along Sumatra/Java
and the Bay of Bengal (figure 7). This results in
low sea level anomalies in the eastern equatorial
Indian Ocean and the Bay of Bengal. The anomalous downwelling Rossby waves forced by anticyclonic wind stress curl during IOD events are
seen as high sea level anomalies with northwestsoutheast slope (Rao and Behera 2005).
3.3 Role of salinity
Interannual sea surface salinity variations in the
Indian Ocean are caused both by freshwater
forcing and ocean dynamics (Murtugudde and
Busalacchi 1998; Perigaud et al 2003; Yu and
McCreary 2003; Vinayachandran and Nanjundiah
2009). Interestingly, a coupled model simulation
shows that significant interannual salinity variations in the Indian Ocean occur only during IOD
years (Vinayachandran and Nanjundiah 2009).
Scanty observations of salinity in the tropical
Indian Ocean prevent the identification of the
role of salinity on IOD. However, using OGCMs,
a few researchers have examined the role of salinity on SST during IOD event. The barrier layer
that is present (absent) during normal years in
the eastern (western) equatorial Indian Ocean,
erodes (forms) during positive dipole years as
a response to decreased (enhanced) precipitation
(Murtugudde et al 2000). This feeds back to the
SST in the form of enhanced cooling (warming) due
to strong vertical mixing (shallow mixed layer) in
the eastern (western) Indian Ocean. Masson et al
(2004) examined the role of salinity on equatorial currents. The anomalous easterlies over the
equator drive south equatorial current at surface
and an equatorial under current at subsurface.
The south equatorial current transports the normal
fresh pool westward, increases stratification and
creates a barrier layer in the western equatorial
Indian Ocean. As a result of this shallow stratification, wind mixing is restricted and amplitude of the
momentum increases in the surface layer, resulting
in strengthening of south equatorial current and
continuation of equatorial under current (Masson
et al 2004). These results suggest that there is a
positive feedback between salinity and SST in the
tropical Indian Ocean during a positive IOD event.
3.4 Atmospheric processes
Compared to the southeastern coasts of tropical
Pacific and tropical Atlantic Oceans characterized
by cold SST tongue and low stratus clouds, the
SETIO (off Sumatra) is a region of warm pool
(Vinayachandran and Shetye 1991) with deep convection (Li et al 2003; Gadgil et al 2004). Over
a warm ocean such as the tropical Indian Ocean,
a modest SST anomaly may induce deep convection in situ, so that SST-cloud relation is in
phase (Li et al 2003). Since, a major part of
the tropical Indian Ocean is covered by a warm
pool (SST greater than 28◦ C) (Vinayachandran
and Shetye 1991), the SST-cloud relation is in
phase. On the other hand, in tropical Pacific,
significant phase differences are observed; maximum SST anomalies are observed in the eastern
tropical Pacific during a warm ENSO, but maximum anomaly in convection associated with ENSO
appears in the central Pacific. In-phase SST-cloud
relation in tropical Indian Ocean leads to negative feedback between the atmosphere and ocean.
As cloud amounts increase in the tropical Indian
Ocean, in response to the increase in SST, the
net downward shortwave radiation decreases and
cools the SST (Li et al 2003). Another thermodynamic air-sea feedback in the SETIO is the Bjerknes feedback mechanism. For example, a drop in
SST in the SETIO implies a corresponding drop in
cloud amount in situ. A decrease in atmospheric
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
Figure 8. Schematic of coupled positive feedback in the
southeastern equatorial Indian Ocean. Modified after Li et al
(2003).
convection leads to development of descending
Rossby waves to the west (Gill 1980), resulting
in an anomalous anticyclonic circulation to the
west of decreased convection center. Since, winds
along SETIO are southeasterly during the development phase of IOD, the anticyclonic circulation
enhances wind speeds in the SETIO. The enhanced
winds, in addition to driving coastal upwelling and
vertical mixing, induce strong evaporative cooling of the sea surface, leading to more cooling of
the SETIO (figure 8). This positive feedback acts
only during boreal summer, as mean winds along
SETIO reverse in the fall. During strong IOD years
(such as 1994 and 1997), seasonal southeasterlies
associated with the Asian summer monsoon reinforce coastal upwelling associated with the IOD
near Sumatra in boreal summer and fall, assisting in initiation and strengthening of these events
(Halkides et al 2006). On the other hand, boreal
fall equatorial westerlies deepen the thermocline in
the eastern basin, reducing the cold SSTA in the
eastern equatorial region and near Sumatra and
Java. Such a process contributed to the early termination of the 1994 IOD. Seasonal reversal of monsoon winds during boreal winter reduces coastal
upwelling along Sumatra and Java, contributing
further to IOD termination.
3.5 Intraseasonal oscillation
Madden and Julian (1972) first reported variability at time scales of 30–60 day in zonal winds and
convection, popularly known as MJO. Anomalous
convection first develops in western tropical Indian
Ocean, propagates eastward across the Indian
Ocean and maritime continent, and then decays
east of 180◦ E. Associated with the propagating
anomalous convection, baroclinic circulation anomalies in the wind field are excited; easterlies
(westerlies) to the east (west) of the anomalous
convection in the lower (upper) troposphere. In
the suppressed convection phase of MJO, baroclinic circulation anomalies also occur in the
atmosphere with opposite directions. The MJO
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activity becomes weak during IOD years in
response to the strong subsidence in the SETIO
(Rao and Yamagata 2004). During pure IOD
events, MJO appears before the termination of
IOD and the associated westerlies, anomalous
downwelling Kelvin waves and deepens the thermocline in the SETIO, arresting air-sea coupling.
Suppressed convection phase of MJO, associated
with equatorial easterly wind anomalies, can trigger an IOD event by exciting anomalous upwelling
Kelvin waves (Han et al 2006; Rao et al 2009).
Their model simulations suggested that before
the onset of the strong 1997 dipole, basin-wide
wind-driven oceanic resonance with a period near
90 days, involving the propagation of equatorial
Kelvin and first-meridional-mode Rossby waves
across the basin, was excited. Associated with the
resonance was a deepened thermocline in the eastern basin during August and early September,
which reduced the upwelling in the eastern antinode of the IOD, thereby delaying the reversal of
the equatorial zonal SST gradient – an important
indicator of a strong IOD – by over a month compared to 1994 IOD event.
4. Dependence of IOD on El Nino
4.1 Observations
The mean thermocline in the Indian Ocean is deep,
compared to the Pacific. Therefore, initiation of
a coupled phenomenon that involves shallowing of
the thermocline (so that the subsurface ocean can
interact with the SST through wind mixing) is
considered to be an uphill task. This conviction
led to the tenet that the Indian Ocean is passive
and merely responds to the atmosphere (Kiladis
and Diaz 1989; Venzke et al 2000; Alexander et al
2002), and interannual variability of the Indian
Ocean SST are forced mainly by ENSO, through
an atmospheric bridge (Klein 1999; Alexander et al
2002). The bridge is through Walker circulation
which, climatologically, has ascending motion over
the western Pacific and maritime continent, and
descending motion over eastern Pacific. This normal Walker cell reverses during ENSO, with strong
descending motion over western Pacific and equatorial Indian Ocean. About 4 months after largescale SST anomalies are observed in the equatorial
Pacific, the whole of the Indian Ocean is covered
with SST anomalies of the same sign. The warming
(cooling) of the Indian Ocean during warm (cool)
phase of ENSO is usually basin-wide and mainly
due to surface heat fluxes (Klein et al 1999; Venzke
et al 2000). The 4 month delay for the Indian Ocean
to warm in response to ENSO is due to the thermal
inertia of the ocean surface layer. The Indian Ocean
578
P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
warming associated with ENSO, however, is not
basin-wide at all stages of ENSO. In the early
stages of development of an ENSO, there are cold
SSTA in the eastern equatorial Indian Ocean but
they disappear as El Nino matures (Rasmusson and
Carpenter 1982; Huang and Kinter 2002; Hendon
2003; Krishnamurthy and Kirtman 2003).
Simultaneous correlations between SSTA in the
eastern Indian Ocean and ENSO indices tend to
suggest that IOD events are forced by ENSO
(Allan et al 2001; Baquero-Bernal et al 2002; Xie
et al 2002; Hastenrath 2002; Krishnamurthy and
Kirtman 2003; Annamalai et al 2003). The strong
IOD event of the recent times that occurred during
1997 coincided with a very strong ENSO. However,
IODs have occurred together with ENSO as well
as independently, and SSTA caused by ENSO lack
the dipole pattern as during the IOD events. Moreover, anomalies associated with IOD are phaselocked to the seasonal cycle, they appear during
boreal summer and fall, whereas, basin-wide anomalies associated with ENSO appear mostly during
winter and spring (Tozuka et al 2008). EOF of
SST anomalies shows a basin-wide pattern as the
first mode due to the effects of ENSO. The second
mode, on the other hand, shows remarkable seasaw between the eastern and western Indian Ocean
which is due to the IOD and this mode is independent of ENSO (Yamagata et al 2004). About 50
percent of the IOD events have occurred together
with ENSO and the rest independently (Saji and
Yamagata 2003; Meyers et al 2007). Clearly, the
ocean-atmosphere coupling intrinsic to the Indian
Ocean can lead to the development of an IOD event
(Saji et al 1999; Yamagata et al 2003, 2004; Behera
et al 2006; Chang et al 2006; Schott et al 2009).
4.2 Coupled models
Coupled ocean-atmosphere general circulation
models have been successful in reproducing the
IOD events, as illustrated first by Iizuka et al
(2000) and characteristics of IODs simulated by
coupled models are comparable to that seen in
observations (Iizuka et al 2000; Baquero-Bernal
et al 2002; Lau and Nath 2004; Cai et al 2005;
Behera et al 2006; Song et al 2007). The major issue
that has been addressed using such models is to
test whether IOD is generated by processes intrinsic to the Indian Ocean or by external forcing from
the Pacific.
In a coupled simulation for 50 years (Iizuka
et al 2000), the model generated 8 IODs compared to 20 IOD events in a 100 year simulation
using CCSM 2 (Vinayachandran and Nanjundiah
2009). Iizuka et al (2000) found poor correlation
between DMI and SSTA in the NINO3 region
and concluded that the IOD in this model is
independent of ENSO. Bequero-Bernal et al (2002)
carried out two simulations using a coupled model,
first with effects of El Nino included and then
excluded. They concluded that dipole like variability in the model is forced primarily by ENSO
but they also found that the model additionally
generates a dipole structure forced by atmospheric
fluxes, independent of ENSO. The SINTEX model
simulation had 20 IODs in its 80 year model integration (Gualdi et al 2003). The peak model SSTA
associated with the IOD occurred about 3 months
before the SSTA peak in the NINO3 region suggesting that IOD evolution in the model is generally independent of ENSO. However, the model
results suggested that sea level pressure anomalies
associated with ENSO might produce atmospheric
conditions that are favourable for the generation of
IOD. In the GFDL coupled model simulations (Lau
and Nath 2004), IOD pattern was caused primarily
by ENSO; changes in surface wind field over the
Indian Ocean associated with ENSO modify both
air-sea fluxes and oceanic process leading to dipole
SST pattern. The model also produced strong IOD
events in the absence of ENSO and these were
caused by an annular mode associated with sea
level pressure anomalies south of Australia. Using
the SINTEX model, Fischer et al (2005) carried
out a coupled model experiment in which the
effect of ENSO was suppressed by constraining
wind stress over tropical Pacific. The IOD in this
simulation was identical to the run that included
ENSO. Modifying the SST field to suppress ENSO
(Behera et al 2006) in the same model yielded
a similar result. The IOD events in the GFDL
CM2.1 coupled model are preceded by anomalous
conditions in the west Pacific warm pool, marked
by an eastward shift in convection, westerly winds
and SST (Song et al 2007) suggesting that variations in Indo-Pacific warm pool are crucial for
generating IOD conditions. From process experiments, they concluded that IOD forms as a result
of processes intrinsic to the Indian Ocean. They
also noted that IODs can also be caused by ENSO
even though the number of cases of the latter
is relatively smaller. The CSIRO Mark 3 coupled
model produced 74 ENSO and 34 IOD events out
of 240 years of model simulation (Cai et al 2005).
Among these, there were only occasional coincidence of IOD and ENSO, whereas 23 IOD events
occurred one year after ENSO. Unrealistic interactions between the Indian and Pacific Oceans lead
to development of such IOD events (Cai et al 2005)
suggesting that mechanism that leads to the formation of IOD like events in coupled models needs
further investigation.
In summary, both observations and models
agree that it is not necessary to have forcing
by ENSO in order to generate an IOD. That
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
is, the Indian Ocean can support its own air-sea
interaction process. A crucial role in the evolution of the IOD is played by the interaction
of the thermocline with the SST. The slope of
the thermocline in coupled models show considerable variation between models (Saji et al 2006)
and the frequency of occurrence of IOD in these
models is crucially dependent on the shape of the
thermocline. In ocean-atmosphere coupled models,
dynamical coupling takes place through wind stress
and thermodynamic coupling through SST and
air-sea heat flux. Thus generation of ENSO in a
coupled model can be suppressed by not allowing the atmosphere to interact with the model
SST. This is typically achieved by replacing model
SST with climatology (Elliot et al 2001; BequeroBernal et al 2002; Behera et al 2005). The dynamical coupling through wind stress is present in such
experiments, which can produce a Bjerknes type
of feed back in the presence of a shallow thermocline. Consequently, oceanic variability associated
with ENSO is not well suppressed and influences
oceanic regions in the SETIO (Fischer et al 2005).
A second method also has been used (Fischer
et al 2005), in which, the dynamical coupling
is suppressed by prescribing climatological wind
stress in the tropical Pacific. This constraint
removes the atmospheric signals associated with
ENSO and reduces the oceanic signals dramatically (Fischer et al 2005). Considering that oceanic
processes associated with the IOD can evolve even
in the absence of Indonesian through flow (ITF)
(Vinayachandran et al 2007), the latter method
could be considered as the preferred mode of suppressing ENSO in coupled models.
5. Triggering
Evolution of the 1997–98 event together with an
El Nino prompted the hypothesis that ENSO can
induce contrasting wind anomalies in the equatorial Indian Ocean which can mature into an
IOD (Ueda and Matsumoto 2001). This mechanism, however, is not capable of explaining all
IODs, particularly those formed during non-ENSO
years. Signatures of IOD events begin to appear in
spring (March-April) and therefore, several studies have explored a mechanism that could induce
easterly wind anomalies along the equator and
southeasterlies off Sumatra. Spring rainfall in the
eastern equatorial Indian Ocean (EEIO) is simultaneously correlated with the west-central Pacific
SSTA and unrelated to local SSTA (Annamalai
et al 2003). Based on this, Annamalai et al (2003)
have proposed that initiation of the IOD takes
place in boreal spring which is the time window
through which external forcing from the Pacific
579
can influence the Indian Ocean. In this mechanism,
warm SSTA in west-central Pacific modifies the
Walker circulation and leads to subsidence over the
EEIO and the IOD grows by the Bjerknes feedback. However, their experiments with an AGCM
showed rather weak response of the EEIO rainfall
to west-central Pacific SSTA and no attempt was
made to demonstrate that SST and thermocline
depth anomalies evolve into conditions favourable
for the IOD. According to Kajikawa et al (2001),
intensification of the Hadley cell over the western
Pacific can enhance the southeasterly in the EEIO,
SST cooling and suppression of convection, triggering an IOD. The intensification takes place during
summer and can be either due to ENSO or monsoon. However, wind anomalies associated with the
IODs appear during spring (Vinayachandran et al
1999, 2007) which the above mechanism fails to
explain.
Fischer et al (2005) examined triggering mechanisms of IOD in the presence as well as absence
of El Nino using a coupled model. In the presence of ENSO, as the convection shifts eastward
in the Pacific during the development of ENSO,
easterly wind anomalies occur in the eastern Indian
Ocean and the thermocline becomes shallow. This
is followed by development of upwelling favorable winds and reduced precipitation, triggering
the growth of an IOD. In the absence of ENSO,
the trigger originates from an anomaly in Hadley
circulation during April-May featuring southerly
cross equatorial winds and reduced rainfall in the
SETIO, completely independent of atmospheric
and oceanic processes in the Pacific. Interestingly,
these are preceded by anomalies of SSTA in MarchApril suggesting that the trigger originates in the
ocean.
In quite a deviation from all other theories,
Francis et al (2007) proposed that cyclones over the
Bay of Bengal during spring season can trigger IOD
events. Initiation of suppressed convection in the
SETIO is caused by meridional pressure gradients
created by severe cyclones over the bay. The development of this anomalous convection into IOD is
effected by the fact that suppression of convection
in the east is associated with enhancement of convection in the west (Gadgil et al 2003, 2004), the
former leading to southeasterlies off Sumatra and
easterlies over EIO.
IOD events are preceded by a downwelling
Rossby wave that originates from the eastern
boundary (Vinayachandran et al 2002). These
waves precondition the western equatorial Indian
ocean by deepening the theremocline. Such wave
propagations during 1993 and 1996 provided a
favourable background for the evolution of the
IOD events during 1994 and 1997, respectively.
Rossby waves can also excite a Kelvin wave which
580
P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
preconditions the thermocline in the eastern Indian
Ocean as in the case of 2003 and 2006 (Rao et al
2009). Intensification of the northward portion of
the ITCZ in March or a suppressed convection
phase of an MJO can also restrict convection,
triggering an IOD (Rao et al 2009).
A key parameter involved in the coupled ocean
atmosphere interaction culminating in the IOD
is depth of the thermocline (Li et al 2003).
A shallow thermocline in the east is a necessary
condition for upwelling to work efficiently to cool
the SST (Vinayachandran et al 1999, 2002, 2007;
Murtugudde et al 2000). Therefore, preconditioning of thermocline provides a favourable background, and, probably, a necessary condition for
the formation of IOD (Annamalai et al 2005). The
pre-conditioning of the Indian Ocean can be caused
by Pacific decadal variability, which can influence the Indian Ocean either through atmosphere
or through the ITF (Annamalai and Murtugudde
2004). The former is effected through zonal wind
anomalies along the equator and an anticyclone to
the east of Sumatra, and the latter by the influence of ITF on the thermocline (Annamalai et al
2005). Consequently, IOD events are stronger in
decades during which Pacific decadal variability
favors a shallow thermocline in the SETIO such as
the 1960s and 1990s.
Being a coupled ocean-atmospheric process, triggering of an IOD can originate either in the ocean
or in atmosphere. All the studies mentioned above,
except Rao et al (2009), point to a trigger from the
atmosphere, either by a modification of the Walker
circulation or of the Hadley cell. This is consistent
with evolution of IOD events in the last decade;
observations suggest that first signs of the IOD
appear as anomalous easterlies along the equator
and anomalous southeasterlies off Sumatra (e.g.
the 2006 IOD event (Vinayachandran et al 2007)).
Shallowness of the thermocline is crucial for further
development of the IOD as it is a crucial parameter for the Bjerknes feedback. There is a nearperfect sea-saw relationship in convection between
the eastern and westen boxes of IOD; whenever
convection is enhanced in the eastern side, it is suppressed in the west and vice versa (Gadgil et al
2003, 2004). Thus, once the thermocline is preconditioned, enhancement of convection either in the
west or in the east can trigger a positive feedback.
6. Influence of the Indian Ocean dipole in
regional climate system
6.1 IOD and east African rainfall
The variability of east African rainfall has profound
impact on the livelihood of millions of people in
Figure 9. Correlation between DMI and precipitation over
the Asian monsoon region. DMI is computed using HadISST
available at (http://badc.nerc.ac.uk) and precipitation used
is CPC merged analysis of precipitation (CMAP) available
at http://iridl.ldeo.columbia.edu.
the developing countries in this region, who mainly
depend on the rain-fed agriculture and regional
fisheries. Relationship between the SST in the
tropical Indian Ocean and the climate in the surrounding regions has been explored by several studies even prior to the discovery of the IOD (Saha
1970; Reverdin et al 1986; Nicholls 1995; Nicholson
and Kim 1997; Goddard and Graham 1999). Many
of these studies focused on the anomalous convection and rainfall in the east African countries in
1961/62 and attributed it to the anomalously warm
western equatorial Indian Ocean. In general, the
influence of Indian Ocean SST tends to dominate
in the rainfall variability of Africa in the warm
phase of ENSO and the Atlantic Ocean controls
the rainfall of Africa in the cold phase (Nicholson
and Kim 1997). Experiments with atmospheric
general circulation models to quantify the relative
influence of the Indian and Pacific Oceans suggest that even though the Pacific SST anomalies
influence the rainfall activity in the African region,
atmospheric response to the Indian Ocean variability is essential for the simulation of correct rainfall
response over central, southern and eastern Africa,
particularly the simulation of observed centraleastern/southern African dipole pattern in rainfall (Goddard and Graham 1999). Interestingly,
there are some studies, which suggest that the teleconnection between the east African rainfall and
ENSO is a manifestation of a link between ENSO
and the IOD (Black et al 2003).
After discovery of the IOD (Saji et al 1999;
Webster et al 1999), several studies have investigated the role of IOD on regulating regional climate. There is a tendency for increased rainfall in
the tropical eastern Africa and drought in Indonesia in IOD years (Saji et al 1999). The correlation between the DMI and precipitation over the
Asian monsoon regime confirms this (figure 9).
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
581
Figure 10. Rainfall maps for Africa in a) November 1961
and b) October 1997. Rainfall data used is global gridded station rainfall data (Chen et al 2002), available at
ftp://ftp.cpc.ncep.noaa.gov/precip/50yr/gauge/0.5deg.
The extreme floods in East African countries in
1961–62 and 1997–98 (figure 10) were associated
with anomalous conditions in the Indian Ocean
(Saji et al 1999; Webster et al 1999; Birkett et al
1999; Saji and Yamagata 2003). Extreme flood
conditions in the east-African region in 1997–98
cannot be attributed to an exaggerated response to
the El Nino as the correlation between the east
African rainfall and the central Pacific SST is only
0.24 (Webster et al 1999; Latif et al 1999). Further, a similar flood in 1961–62 did not co-occur
with an El Nino. Enhanced rain in the east African
region is associated with increased moisture convergence due to strong westerlies over the central
Africa and easterlies from the equatorial Indian
Ocean as a response of warm western pole of the
IOD (Ummenhofer et al 2009). SST anomaly in
western pole of the IOD has more impact on the
east African short rains compared to that of the
east pole (Ummenhofer et al 2009), these SST
anomalies result from the strong sub-surface influence due to propagating Rossby waves related to
the IOD events (Rao and Behera 2005). This slowly
propagating air-sea coupled mode could be an indicator for the prediction of the IOD induced short
rain events well in advance. Atmospheric and coupled ocean-atmosphere general circulation models
have been able to simulate the observed association
between the DMI and east African rainfall reasonably well (Behera et al 2003; Conway et al 2006).
Hence coupled models also may be used to predict
east African short rains.
6.2 IOD and Indian summer monsoon rainfall
A major advance in our understanding of the
interannual variation of the Indian summer monsoon rainfall (ISMR) occurred during the 1980s,
with the discovery of a strong link with El Nino
and Southern Oscillation (ENSO), the dominant
signal of interannual variation of the coupled
ocean-atmosphere system over the Pacific (Sikka
1980; Pant and Parthasarthy 1981; Rasmusson and
Figure 11. Scatter diagram of normalized ISMR anomaly versus Nino 3.4 SST anomaly. Both anomalies are
normalized by their respective standard deviations. ISMR
data is obtained from http://tropmet.res.in and NINO 3.4
index is obtained from http://www.cpc.noaa.gov/data/
indices/sstoi.indices.
Carpenter 1983). There is a high propensity of
deficit monsoon during warm ENSO events, with
deficit in 21 out of 25 such events during 1875–
1979, which included 9 of 11 seasons with largest
anomalies (Rasmusson and Carpenter 1983). It can
be seen from figure 11 that this is true in general.
However, while majority of the droughts are associated with a positive Nino 3.4 index (El Nino condition), there are droughts of 1974 and 1985 which
are associated with negative SST anomaly in the
Nino 3.4 region. The NINO 3.4 index is very small
in the drought years such as 1966, 1968 and 1979.
Again, while in majority of the excess monsoon
seasons, SST anomaly in the Nino 3.4 region is
negative (La Nina condition), it is positive in 1983
and 1994. Further, in 1997, during the strongest
El Nino year in the century, the ISMR was above
normal. Consequently, Kumar et al (1999) suggested that the relationship between the Indian
monsoon and ENSO had weakened in the recent
decades.
The correlation between DMI and ISMR is
rather weak (figure 9). However, if we consider
case by case, out of the 11 intense (anomalies in
DMI more than one standard deviation) positive
IOD events that occurred during 1958–1997, eight
events (1961, 1963, 1967, 1977, 1983, 1994, 1993
and 1997; i.e. 73% of the positive IOD events during this period) are associated with positive anomalies of the concurrent ISMR (Ashok et al 2001).
Similarly, out of the three negative IOD events
during 1958–97, two events (1960 and 1992) correspond to negative anomalies of the ISMR. Interestingly, the sliding correlation between the ISMR and
ENSO has an opposite tendency to that between
582
P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
Figure 12. 41-month sliding correlations between NINO3
index and ISMR (dashed curve, multiplied by −1) and DMI
and ISMR (solid curve). Correlation coefficient of 0.38 is
significant at 90% (after Ashok et al 2001).
ISMR and IOD; i.e., when the ISMR-ENSO (negative) correlation is strong, ISMR-IOD (positive)
correlation is weak. Similarly, when the ISMR has
a strong positive correlation with IOD, the relation
between ENSO and ISMR is weak as seen from
figure 12. This strong positive relation between the
IOD and ISMR during 1960s and 1990s could be
one of the reasons for excess monsoon seasons in
1961, 1994 and near normal monsoon in 1997. However, neither the ENSO nor the IOD can explain
all the excess/droughts in the Indian summer monsoon. For example, drought years of 1985 and 1974
are not associated with negative IOD or El Nino.
The droughts during 1966, 1968, and 1979 are associated with very small SST anomalies in the central Pacific and no IOD signal in the Indian Ocean.
Hence, even though a few modeling studies with
AGCMs and coupled OAGCMs also suggest that
the positive IOD events can intensify the Indian
summer monsoon rainfall (Ashok et al 2001, 2004;
Guan and Yamagata 2003; Guan et al 2003), we
still need to understand the role of IOD in the interannual variation of the ISMR.
6.3 ISMR and equatorial Indian Ocean oscillation
The extreme drought in 2002 and the very fact that
none of the predictions (irrespective of whether
it is using complex GCMs or empirical models)
could anticipate this drought, triggered debates
among researchers around the world on the factors influencing the ISMR variability. This drought
was neither associated with a very strong El Nino
or a negative IOD event (Gadgil et al 2002). Subsequent to this monsoon failure, in 2003, the ISMR
was very close to its long term mean. Interestingly, the July mean outgoing longwave radiation
(OLR) (which may be used as a proxy for tropical convection) pattern over the Indian region and
the equatorial Indian Ocean in 2003 was exactly
opposite to that in 2002 (figure 13a & b). In 2002,
there was a high OLR anomaly over the western
part of the Indian region and the western equatorial Indian Ocean (WEIO). At the same time
OLR anomaly was negative (indicating more convection) over the EEIO. The pattern was just the
opposite in 2003. These are not isolated events. In
fact, the OLR anomaly patterns in the monsoon
months of 1986 and 1994 are quite similar to that
in 2002 and 2003, respectively (figure 13c & d).
Gadgil et al (2004) termed this oscillation in the
convection over the WEIO and EEIO as the equatorial Indian Ocean oscillation (EQUINOO). They
suggested that the winds along the equatorial
Indian Ocean could be considered as a measure
of the intensity of the EQUINOO as it responds
to the pressure gradient associated with differential heating in the atmosphere due to the difference in convection. EQUINOO index (EQWIN)
is defined as the negative of zonal wind anomaly over central equatorial Indian Ocean (averaged
over 60◦ E–90◦ E, 2.5◦ S–2.5◦ N). The IOD is a coupled phenomenon and its signatures are seen in
convection and surface wind over the equatorial
Indian Ocean also (Saji et al 1999). Interestingly,
there are occasions on which such convection and
surface wind anomalies are present without an SST
dipole signal (Francis 2006). Hence, even though
all the IOD events are associated with EQUINOO,
the reverse is not necessarily true.
When the relative influence of EQUINOO and
IOD on ISMR is considered, the ISMR is better
correlated to the EQUINOO than IOD (Gadgil
et al 2004). The relation of ISMR with EQWIN
and DMI is shown in figure 14a&b. The DMIISMR correlation is only 0.05. On the other hand,
EQWIN-ISMR correlation is significantly high
(0.45). While the ISMR is negatively correlated to
the OLR over the WEIO, it is positively correlated
to OLR over the EEIO (figure 15). Hence, an excess
(drought) monsoon is associated with enhanced
(suppressed) convection over the WEIO and suppressed (enhanced) convection over the EEIO. In
other words, a positive EQUINOO is favourable
for Indian monsoon and a negative EQUINOO
highly unfavourable. All the excess/drought monsoon seasons in the period 1958–2003 are associated with the favourable/unfavourable phase of
either ENSO or EQUINOO or both (Gadgil et al
2004). There is a clear separation between excess
and drought seasons when represented in the phase
plane of the EQWIN and ENSO indices (which
is the negative of normalized SST anomaly in the
NINO3.4 region) as shown in figure 16. The linear reconstruction of ISMR on the basis of multiple
regression from NINO3 index and the zonal wind
over the equatorial Indian Ocean better specifies
the ISMR than the regression with only NINO3
index (Ihara 2007). Clearly, monitoring and predicting the EQUINOO and IOD is essential for the
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
583
Figure 13. NOAA AVHRR OLR (Wm−2 ) anomaly patterns for a) July 2002, b) July 2003, c) August 1986 and d) August
1994. Data is obtained from http://www.cdc.noaa.gov.
Figure 14. Scatter plot of ISMR versus a) EQWIN and b) DMI. EQWIN is computed from the monthly mean surface
wind data from NCEP reanalysis, available at http://www.cdc.noaa.gov.
prediction of the ISMR. Even though the association between the EQUINOO and the extremes
of ISMR is now established, the mechanism by
which the EQUINOO influences the Indian monsoon is yet to be understood. One explanation for
the increased rainfall in activity over the Indian
region during the positive IOD event is through
the enhanced cross-equatorial flow to the Bay of
Bengal due to the strong meridional SST gradient across the EEIO (Guan 2003). However, during most of IOD events, the largest precipitation
and convection anomalies are observed in the western part of the country (figure 13). More focused
research is required to address this problem.
6.4 IOD and Australian rainfall
The years of extensive Australian drought were
associated with generally low SST in the low latitudes of eastern Indian Ocean (Streten 1981, 1983).
The rainfall over much of Australia tends to be
Figure 15. Correlation between ISMR and OLR over
the Indian monsoon region. Since lower OLR values correspond to deeper convection, negative correlation implies
enhanced (suppressed) convection associated with above
normal (below normal) ISMR.
584
P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
Figure 16. Extremes of the ISMR is represented in the phase-plane of EQWIN and ENSO index (both indices are
normalized by their respective standard deviations) in the period 1958–2008. Color code: dark red, red, blue and dark
blue closed circles represent ISMR anomaly larger than −1.5 standard deviation, between −1.5 and −1 standard deviation,
between 1 and 1.5 standard deviation, and larger than 1.5 standard deviation, respectively. Adapted from Gadgil et al
(2004).
below average during El Nino events (Ropelewski
and Halpert 1987). However, in some El Nino
events (such as 1986/87), Australian rainfall anomalies are weak or of limited extent while in others
(such as 1982/83), the anomalies are major and
widespread (Nicholls 1989). The first pattern of the
principal component analysis of Australian winter
rainfall shows a broad band stretching from the
northwest to southeast corners. This is best related
to the difference in SST between the Indonesian
region and the central Indian Ocean (Nicholls
1989), which is in fact very strong during the IOD
years. This suggests that the El Nino events that
co-occur with IOD are generally associated with
severe droughts in Australia. The negative correlation between the Australian rainfall and Indian
Ocean variability has been successfully simulated
by AGCMs (Ashok et al 2003; Ummenhofer et al
2008). Cold SST anomalies prevailing west of
the Indonesian archipelago during the IOD events
introduce an anomalous anticyclonic circulation at
lower levels over Australia, which in turn reduce
the rainfall activity over this region (Ashok et al
2003).
6.5 IOD and intraseasonal oscillations
An active MJO is characterized by slow eastward
movement of stronger than average precipitation
and westerly winds (Madden and Julian 1972). In
summer monsoon months (June-September), rainfall and wind anomalies also propagate northward
on intraseasonal time scale over India, southeast
and east Asia and the adjacent oceans (Sikka and
Gadgil 1980; Yasunari 1980). Both these propagations are strongly modulated by the IOD (Shinoda
and Han 2005; Ajayamohan et al 2008, 2009).
During the active phase of IOD no significant
intraseasonal oscillations occur in Indian Ocean
equatorial zonal winds (Rao and Yamagata 2004)
and 6–90 day oscillations in winds and OLR tend to
weaken (Shinoda and Han 2005). During negative
dipole years, submonthly (6–30 day) convection
generated in the southeast Indian Ocean is associated with a cyclonic circulation. These submonthly
disturbances propagate southwestward, which generate equatorial westerly winds in the eastern and
central Indian Ocean and northwesterlies near the
coast of Sumatra. During large positive dipole
years, submonthly convective activity is largely
suppressed in the southeast Indian Ocean and
thus no equatorial westerly is generated. The poleward propagation of intraseasonal oscillations during summer monsoon is coherent (incoherent) from
5◦ S to 25◦ N during negative (positive) IOD years
(figure 17). The mean structure of moisture convergence and meridional specific humidity distribution undergoes radical changes in contrasting
IOD years, which in turn influences the meridional
propagation of boreal summer intraseasonal oscillations (Ajayamohan and Rao 2008; Ajayamohan
et al 2009).
6.6 IOD and other global teleconnections
The influence of IOD on other global climate systems is far less explored. One major difficulty is
that many of the positive IOD events in the recent
INDIAN OCEAN DIPOLE: PROCESSES AND IMPACTS
585
Figure 17. (a) Regressed filtered anomalies of CMAP precipitation (mm day−1 ) averaged over 70–95◦ E as a function
of latitude and time lag during the 1980–2004 period. As in (a) but for (b) negative and for (c) positive IOD years.
Contour interval is 0.6. Only statistically significant (0.1 significance level using a t test) anomalies are plotted (taken from
Ajayamohan et al 2008).
years are associated with strong El Nino events and
it is difficult to separate the influence of IOD from
El Nino. Nevertheless, when the influence of ENSO
is removed, in the tropical regions surrounding the
Indian Ocean, there is a clear pattern of warm
temperature anomalies over land regions to the
west and cool anomalies over regions to the east
of the Indian Ocean (Saji and Yamagata 2003).
Over the extratropics, IOD is associated with warm
temperature anomalies, reduced rainfall and positive geopotential height anomalies. The interannual variation of rainfall over central Brazil and
subtropical La Plata Basin during austral spring
is found to be influenced by the IOD, with a positive IOD associated with increased rainfall over
the subtropical La Plata Basin, while it is associated with decreased rainfall over central Brazil
(Chan et al 2008). Another impact of the IOD is on
the ‘maha’ rainfall in Sri Lanka during September
to December. Warm SST anomalies in the WEIO
associated with the IOD event lead to enhanced
convergence in the lower troposphere over the
WEIO, which in fact, extends up to Sri Lanka
(Lareef et al 2003). This leads to increased rainfall activity over Sri Lanka. In general, El Nino
events also lead to increase in the ‘maha’ rainfall (Rasmusson and Carpenter 1983; Ropelewski
and Halpert 1987). Thus, the influence of IOD and
ENSO on the Sri Lankan rainfall is inter-linked.
However, the influence of IOD is highly significant even when the ENSO influence is statistically
removed (Lareef et al 2003). Some of the recent
studies suggest that the evolution of the ENSO
itself is influenced by the SST variations in the
Indian Ocean (Yu et al 2002), in particular the
IOD events (Behera and Yamagata 2003; Annamalai et al 2005). Thus, the influences of the IOD
events are not restricted on the regional climate.
The mechanisms of the global teleconnections of
the IOD events are yet to be understood clearly.
7. Concluding remarks
ENSO, which is the dominant signal of tropical
interannual variability has significant influence on
the Indian Ocean. Research in the last decade
clearly demonstrates that the IOD is a major signal
of interannual climate variations in the region. The
question whether IOD is independent of ENSO or
not has been debated long and it turns out that the
Indian Ocean can breed and nurture its own IOD
by coupled air-sea processes, without being forced
externally by the Pacific Ocean. Both analysis of
observations and model simulations converge to the
fact that IOD can be generated either by ENSO
or otherwise. There is a general consensus that
the modification of Walker cell during ENSO is
associated with subsidence over SETIO which suppresses convection and can trigger a positive feed
back leading to the development of an IOD. Mechanism that causes IOD formation in the absence
of ENSO is still unclear, although there are indications that anomalies in Hadley circulation holds
the key. Observations suggest that subsurface temperature anomalies, accompanied by strong westward current anomalies appear about 3 months
before the SSTA (Horii et al 2008; Nagura and
McPhaden 2008). Whether the preconditioning of
the ocean, with a lifted thermocline in the east,
is a necessary condition is yet to be established.
This aspect is of particular relevance to the recent
intensification of IOD activity and monsoon-IOD
feedback (Abram et al 2008).
Following the availability of high quality sea
surface wind data, ocean models have been able
586
P N VINAYACHANDRAN, P A FRANCIS AND S A RAO
to reproduce the IOD events remarkably well
(Murtugudde et al 2000; Vinayachandran et al
2007). Coupled-models, on the other hand, have
several limitations. Simulation of the cold tongue
in the Pacific and the shape of thermocline in the
Indian Ocean are poor (Zhong et al 2005; Saji et al
2006). These two are important factors affecting
the simulation of IOD and its dependence on ENSO
need to be carefully evaluated and improved. As
noted by Cai et al (2005), unrealistic interactions
between Indian and Pacific Oceans can occur in
coupled models, and this finding calls for careful
evaluation of processes in coupled models.
The eastern pole of the IOD is quite robust in
its location that is anchored by coastal upwelling
to the west of Sumatra. Consequently, the focus
of process studies has mostly concentrated in the
east. The west, on the other hand, has been less
organized with regard to SST anomalies. Interestingly, convection emanating from the western pole
of IOD and its movement towards the west coast of
India has been a striking feature during IOD events
(Gadgil et al 2004). Further, convection over the
eastern and western Indian Ocean during the monsoon behaves like a sea-saw; enhancement of one is
associated with the suppression of the other. There
is a need to understand the ocean-atmosphere coupling in this region, particularly during the summer
monsoon and its probable role in taking IOD events
to maturity through its control over atmospheric
convection.
Impact of IOD on the climate of Asia, Africa
and Australia is significant and, therefore, it is
absolutely necessary that the scientific community
be able to forecast its evolution well in advance.
Considering that this is a fully coupled phenomenon, a coupled model is a basic requirement.
The strong IOD event of 2006 (Vinayachandran
et al 2007) was successfully predicted by a coupled
model but it had limited success in forecasting the
evolution of the weak IOD event of 2007 (Luo et al
2008). Extremes of the Indian summer monsoon
are found to coincide with the positive and negative
IOD (Gadgil et al 2003, 2004) and therefore urgent
need for a forecast arises from the Indian subcontinent. Result of forecasting experiments (Luo et al
2008) are encouraging and the usefulness of such
a system for Indian summer monsoon as well as
other regions where IOD affects rainfall, is yet to
be tested and put into practice.
Acknowledgements
This study was funded by the Indian Ocean
Modeling Program (INDOMOD), Indian National
Centre for Ocean Information Services (INCOIS),
Ministry of Earth Sciences, Government of India.
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